This project was developed in direct support of AlMaktaba AlSagheera, a B2B retail company operating in the Egyptian market. The company specializes in supplying stationery and books to supermarket chains. Its value proposition lies in offering a turnkey solution that enables supermarkets to start selling these products immediately, without having to manage complex logistics or establish extensive supply chain operations. Even a small supermarket branch can have a fully functional stationery and book stand from day one.
When the company was founded in 2019, following a partnership with one of Egypt’s largest supermarket chains, Gomla Market, all operations were handled using a paper-based legacy system. At that point, I initiated a digital transformation project to build an integrated, cloud-based ERP system tailored to the company’s needs.
System Overview
The core of the new system was based on Odoo, a modular ERP platform. This system was synchronized with two separate Woocommerce databases:
The data generated by these systems was analyzed and reported through a combination of Excel and Power BI. A significant part of the project involved developing a robust data analytics system that streamlined the flow of sales and inventory data, cleaned and profiled it automatically, and generated actionable insights for decision-making.
Data Analytics System Components
The analytics workflow focused on automating data profiling and cleaning while enabling predictive decision-making. The key components of the system included:
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Sales Data Ingestion
Sales data from supermarket clients was collected monthly, coinciding with revenue collection cycles. This data often arrived in inconsistent formats, and in some cases as scanned documents. The system was designed to ingest, clean, and standardize this data automatically. -
Automated Data Cleaning and Profiling
A custom Excel-based pipeline cleaned and structured the incoming data. Each item was assigned key internal variables, including:- Main and sub-category
- Supplier details
- Cost price (including overhead)
- Price range for sale
- Internal warehouse and logistical coordinates
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Supplier Reporting
For suppliers operating under a credit-based payment model, the system automatically generated and exported detailed sales reports. -
Visual Reporting with Power BI
The cleaned data was then fed into Power BI dashboards to visualize performance. Reports analyzed how different product sub-categories and price ranges performed across branches. This enabled the company to identify high-performing product segments at specific locations. -
Inventory Synchronization
Real-time inventory data from the central warehouse was integrated into the system to identify which products needed restocking. A key insight here was that products were grouped by sub-category and price range, which acted as a unique identifier. This approach accounted for the fact that many stationery products are interchangeable, as long as they meet price and functional requirements. Only well-established brands were tracked as distinct entities. -
Predictive Analytics Pipeline
A predictive analytics module was built using Python. It employed supervised learning models trained on historical data to forecast which products were likely to sell better at each branch in the upcoming month. This allowed the company to optimize shelf displays and allocate display space more efficiently.
Business Impact
The system significantly enhanced AlMaktaba AlSagheera’s ability to deliver on its promise to supermarket clients: maximize revenue and foot traffic using the smallest possible display area. By turning a fragmented and paper-based system into an intelligent, data-driven operation, the company gained a clear edge in retail efficiency and decision-making.
This transformation not only improved internal operations but also strengthened AlMaktaba AlSagheera’s position as a trusted partner for retail clients seeking smart, ready-to-deploy book and stationery sections.